Reorganising health and social care in Québec: a journey towards integrating care through mergers
Bibliographic record
Abstract
CONTEXT: Two reforms (2014, 2015) characterised by the merger of public health care establishments profoundly shaped the current organisation of Quebec's healthcare system. In 2015, 22 megastructures called Integrated Health and Social Services Centres/Integrated University Health and Social Services Centres (IHSSC/IUHSSC), were created and mandated to organise care delivery to their local populations. OBJECTIVE: To describe the service configuration of the 2015 healthcare system reforms, emphasising on how it shaped the organisation of primary health care (PHC) in Quebec. RESULTS: With the creation of IHSSCs/IUHSSCs, Quebec's healthcare system passed from three to two levels of governance, leading to a centralisation of decision-making powers. Most health services are delivered by the new organisations, while most PHC is delivered by semi-private medical practices, mainly Family Medicine Groups (FMGs). The FMG model is the preferred strategy to develop interdisciplinary team-work and inter-organizational collaborations with other PHC services. CONCLUSION: mechanisms through which centralised healthcare systems achieve community oriented integrated care (COIC) need to be properly understood in order to improve meaningful clinical outcomes. Mergers may not sufficiently achieve integration of services in all its dimensions. These reforms should be monitored and evaluated on their capacity to mobilise all providers as well as physicians to participate in COIC.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".